Exploring the IOCT’sExploring the IOCT’sExploring the IOCT slarge fleet of helicopter robots

Mario A Gongora & Benjamin N Passow

Exploring the IOCT slarge fleet of helicopter robots

Mario A Gongora & Benjamin N PassowMario A. Gongora & Benjamin N. PassowMario A. Gongora & Benjamin N. Passow

About usD M i A GDr. Mario A. Gongora

• Senior Lecturer

Benjamin N. Passow• PhD student

Project: Using a fleet of helicopters to:• research aspects of emergent societal behaviours• sonic signatures to identify/control the fleet• Creative way to achieve control?• creativity in behaviour and artistic coordination?

The Fleet

• About 8 xTwister Bell 47 helicopters

• Helicopter properties:• 34 cm rotor span• 210 grams net weight• Max 100 grams payload• Remote controlled• Remote controlled• 4 actuators (2 servos, 2 motors)• flight duration: 10 minutes g

How do they work

Degrees of freedom:• 3 translational• 3 rotational

Controlled by:y• Lift (overall rotors speed)• Heading (difference rotors speed)g ( p )• Pitch (rotor blade angle)• Roll (rotor blade angle)

Difficulties

• Helicopters are unstableand nonlinear systemsy

• Difficult to achieve stability:lik di b ll• like standing on a ball

• …so what do we need to do to:?• Making them autonomous• Letting them dance … without crashing!

Autonomy

• Autonomy = helicopter can control itself without the need for remote control

• Embedded system developed

H li t h• Helicopter can now hoverautonomously using (lightweight):

Di it l• Digital compass• Distances to ground• Classical control methods• Classical control methods• Computation done on-board

HeRo in detailStabilising flybar

Dual Rotors

Digital Compass

Processing unit

(CMPS03)

(Microchip dsPIC30F) 2 strong

DC motors

Battery pack 2 servos

3 Sonar Sensors (SRF08)

(LiPo 7.4V)

What we have

• Current prototypes:• Capable of hovering

at a predefined height

• Future work:• Stable flight manoeuvres• Controlled flight of a whole swarm• Coordination among the swarm• Application in research & performance art

Movie

Restrictions & Limitations

• DANGEROUS! No flying around people! • Limited payloadLimited payload

• Remote: 100 gram max• Autonomous: 60 gram max• Autonomous: 60 gram max

• Limited flight duration: ~10 minutes• Indoor use only

• Due to sensitivity to wind

Optimising the Controller

• Enhance stability byevolving controller’s parameters

• Using Evolutionary Computing (GA)• Optimising 5 parameters of PID controllerp g p• Implemented on host computer• Evaluation on real system

• GA can run fully automatic once started

P ibl l ti l t d l h li t

GA Setup• Possible solutions evaluated on real helicopter

• Helicopter bound to turn-table• Controller to react to artificial perturbation to both sides• Fitness inverse proportional to amount of error to set point

Movie

GA Results

• Found better solution than hand-tuning• Noise and uncertainties

in real system:• Significant variability

l ti i di id lre-evaluating individuals

• Keeping GA running• GA finds more• GA finds more

“consistent” solutions • Less variability Fig. 1. GA (black) and hand tuned (gray) PID

controllers response to heading perturbed by 90◦ aty

and more robustnesscontrollers response to heading perturbed by 90◦ att=0 and -90◦ at t=92. Mean of 12 individual tests foreach controller

Creative Approach

• We need to enhance the stability, achieve in-air synchronisation as well as obstacle avoidance

• Could be done adding many sensors• Helicopter would become too heavyp y

• Instead we use a novel creative approach• Using the intrinsic sound signature of the helicopter• Using the intrinsic sound signature of the helicopter• Not a single additional sensor is needed

Control using Sound

The helicopter’s intrinsic sound signature is recorded andThe helicopter s intrinsic sound signature is recorded and analysed by the HaRT robot

HaRT Robot

• HaRT - Humans and Robots Together• for human-robot interaction

• (it doesn’t attempt to look humanoid)

• Is controlled by super-computer

• Recording and analysingHelicopter sound signatures• HaRT has microphones

to record sound signatures• Super-computer analyses these• Super-computer analyses these

Sound = Information

• Motors and rotors generate vibrations• Vibration = Sound

• Sound acquired by HaRT

• Sound = InformationSound Information• Where is the sound coming from? (Localisation)• The power of the motors reflects on the sound• The difference between motor speeds also affects the

sound• Servos generate sound tooServos generate sound too

Enhance control

• Coordination information is fed back to helicopter using a Bluetooth link• Controller to incorporate this new information

• “Too far left” – Fly to the righth h li l h i h l bi l f• “Other helicopter close to the right” – Fly a bit left

• Etc.

• Benefits:• Enable in-air synchronisation• Enhance stability

Aesthetic Applications• HaRT to translate sonic signatures into musical calls• Swarm of helicopters in formation flight and dancing• Performance art using helicopter’s with coloured

trails• Helicopter reacting to music / dancing (inverse

control of performance)i h li i h li h h d i d k• Dancing helicopters with lights attached in darkness

• Many more…

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